Creating a dataframe from Pandas series
Series is a type of list in pandas which can take integer values, string values, double values and more. But in Pandas Series we return an object in the form of list, having index starting from 0 to n, Where n is the length of values in series.
Later in this article, we will discuss dataframes in pandas, but we first need to understand the main difference between Series and Dataframe. Series can only contain single list with index, whereas dataframe can be made of more than one series or we can say that a dataframe is a collection of series that can be used to analyse the data.
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Code #1: Creating a simple Series
0 Jitender 1 Purnima 2 Arpit 3 Jyoti dtype: object
Let’s check type of Series:
Code #2: Creating Dataframe from Series
Author Article 0 Jitender 210 1 Purnima 211 2 Arpit 114 3 Jyoti 178
We are combining two series Author and Article published. Create a dictionary so that we can combine the metadata for series. Metadata is the data of data that can define the series of values. Pass this dictionary to pandas DataFrame and finally you can see the result as combination of two series i.e for author and number of articles.
Code #3: How to add series externally in dataframe
Author Article Age 0 Jitender 210 21 1 Purnima 211 21 2 Arpit 114 24 3 Jyoti 178 23
We have added one more series externally named as age of the authors, then directly added this series in the pandas dataframe. Remember one thing if any value is missing then by default it will be converted into
NaN value i.e null by default.
Code #4: Missing value in dataframe
Author Article Age 0 Jitender 210 21.0 1 Purnima 211 21.0 2 Arpit 114 23.0 3 Jyoti 178 NaN
Code #5: Data Plot on graph
plot.bar() we have created a bar graph.